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Segmentation Techniques for Computer-Aided Diagnosis of Glaucoma: A Review

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Advances in Machine Learning and Data Science

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 705))

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Abstract

Glaucoma is an eye disease in which the optic nerve head (ONH) is damaged, leading to irreversible loss of vision. Vision loss due to glaucoma can be prevented only if it is detected at an early stage. Early diagnosis of glaucoma is possible by measuring the level of intra-ocular pressure (IOP) and the amount of neuro-retinal rim (NRR) area loss. The diagnosis accuracy depends on the experience and domain knowledge of the ophthalmologist. Hence, automated extraction of features from the retinal fundus images can play a major role for screening of glaucoma. The main aim of this paper is to review the different segmentation algorithms used to develop a computer-aided diagnostic (CAD) system for the detection of glaucoma from fundus images, and additionally, the future work is also highlighted.

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Authors and Affiliations

  1. Department of Information and Communication Technology, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal, 576104, India

    Sumaiya Pathan, Preetham Kumar & Radhika M. Pai

Authors
  1. Sumaiya Pathan
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  2. Preetham Kumar
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  3. Radhika M. Pai
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Corresponding author

Correspondence to Preetham Kumar .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, National Institute of Technology Goa, Goa, India

    Damodar Reddy Edla

  2. Department of Mathematics and Computing Science, Saint Mary’s University, Halifax, NS, Canada

    Pawan Lingras

  3. Department of Computer Science and Engineering, National Institute of Technology Goa, Goa, India

    Venkatanareshbabu K.

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Pathan, S., Kumar, P., Pai, R.M. (2018). Segmentation Techniques for Computer-Aided Diagnosis of Glaucoma: A Review. In: Reddy Edla, D., Lingras, P., Venkatanareshbabu K. (eds) Advances in Machine Learning and Data Science. Advances in Intelligent Systems and Computing, vol 705. Springer, Singapore. https://doi.org/10.1007/978-981-10-8569-7_18

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  • DOI: https://doi.org/10.1007/978-981-10-8569-7_18

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-8568-0

  • Online ISBN: 978-981-10-8569-7

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